CONTEXT–Simulation modelling provides insight into hidden dynamics underlying business processes. However, an accurate understanding of operations is necessary for fidelity of the model. This is challenging because of the need to extract the tacit nature of operational knowledge and facilitate the representation of complex processes and decision-making patterns that do not depend on classes, objects, and instantiations. Commonly used industrial simulation, such as Arena®, does not natively support the object-oriented constructs available for software development. OBJECTIVE–This paper proposes a method for developing simulation models that allow process-owners and modellers to jointly build a series of evolutionary models that improve conceptual validity of the executable computer model. APPROACH-Software and Systems Engineering principles were adapted to develop a framework that allows a systematic transition from conceptual to executable model, which allows multiple perspectives to be simultaneously considered. The framework was applied to a logistics case study in a bulk commodities distribution context. FINDINGS–The method guided the development of a set of models that served as scaffolds to allow the natural flow of ideas from a natural language domain to Arena® code. In doing so, modeller and process-owners at strategic, tactical, and operational levels developed and validated the simulation model. ORIGINALITY—This work provides a framework for structuring the development of simulation models. The framework allows the use of non-object-oriented constructs, making it applicable to SIMAN-based simulation languages and packages as Arena®.